InFormal Chat

Human Learning about Machine Learning in EDA

Needless to say that Machine Learning is a very hot topic nowadays. From the software giants such as Google and Facebook, to hot companies like Snap, Waze and Uber, to traditional businesses such as IBM, ExxonMobil and Toyota to name a few, it seems like all companies need to be talking about Machine Learning. I would not be surprised if every company in the S&P 100 has a list of active Machine Learning projects…or so they say.

Once you start scratching the surface of the press releases and marketing slides, you see that only a fraction of companies have real Machine Learning applications and solutions that match their claims. The same trend and high level of frenzy can be witnessed in EDA, where customers are hungry for innovation.

Synopsys VC Formal also has an interesting set of data about Machine Learning techniques to improve performance and convergence of properties. However, unlike others, there is real technology behind it. I have seen firsthand, some of the early results in this area and the impact is undeniable. I guess it is not surprising when you consider the sheer volume of data that a Formal tool can produce, especially when you start logging regression data. I’m confident that a human with enough time to analyze the data set could also arrive to some meaningful and impactful conclusions. But to get software to do this is in a repeatable manner is truly impressive.

Personally, I became a believer when I first saw a class of properties getting proven with 10X runtime speedup and a second set of benchmarks where some very hard properties finally got proven (after weeks of unsuccessfully trying different manual and automated techniques). That’s when I went form a skeptic to a proponent.

This is not luck or coincidence. Synopsys VC Formal R&D team is led by industry experts who have a rare overlap of both Formal verification and Machine Learning expertise. Dr. Manish Pandey is one of the key architects and he has been working on these class of problems for years, away from the limelight.

Now that the solutions are maturing and being rolled out, Manish is in a position where he can share some of his wisdom with the both the academic and industrial communities. For those who will be in Austin next week (for DAC or IWLS or other reasons), do try to attend one of these two talks on Machine Learning in EDA and Formal Verification. I attended his last talk at FMCAD 2016 and I’m sure you will find it educational …and chances are that you may become a proponent as well.